[R] A possible too old question on significant test of correlationmatrix

[Dimitris Rizopoulos]

you can use function rcor.test() from package 'ltm', e.g.,

help(rcor.test, package = "ltm")
###
library(ltm)

dat <- data.frame(matrix(rnorm(1000), 100, 10))

rcor.test(dat)
rcor.test(dat, method = "kendall")
rcor.test(dat, method = "spearman")


I hope it helps.

Best,
Dimitris

----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/(0)16/336899
Fax: +32/(0)16/337015
Web: http://med.kuleuven.be/biostat/
     http://www.student.kuleuven.be/~m0390867/dimitris.htm



----- Original Message ----- 
From: "Guo Wei-Wei" <wwguocn at gmail.com>
To: <r-help at stat.math.ethz.ch>
Sent: Monday, July 10, 2006 7:27 AM
Subject: [R] A possible too old question on significant test of 
correlationmatrix


> Dear all,
>
> I'm working on a data.frame named en.data, which has n cases and m 
> columns.
> I generate the correlation matrix of en.data by
>
>> cor(en.data)
>
> I find that there is no p-value on each correlation in the 
> correlation
> matrix. I searched in the R-help mail list and found some related
> posts, but I didn't find direct way to solve the problem. Someone 
> said
> to use cor.test() or t.test(). The problem is that cor.test() and
> t.test() can only apply on two vectors, not on a data.frame or a
> matrix.
>
> My solution is
>
> for (i in 1:(ncol(en.data) -1)) {
>   cor.test(en.data[,i], en.data[, i+1])
> }
>
> I think it is a stupid way. Is there a direct way to do so? After 
> all,
> it is a basic function to generate significant level of a 
> correlation
> in a correlation matrix.
>
> Thank you in advance!
> Wei-Wei
>
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